Mostly Harmless Econometrics

Mostly Harmless Econometrics
Author: Joshua D. Angrist
Publisher: Princeton University Press
Total Pages: 392
Release: 2009-01-04
Genre: Business & Economics
ISBN: 0691120358

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In addition to econometric essentials, this book covers important new extensions as well as how to get standard errors right. The authors explain why fancier econometric techniques are typically unnecessary and even dangerous.


Mostly Harmless Econometrics
Language: en
Pages: 392
Authors: Joshua D. Angrist
Categories: Business & Economics
Type: BOOK - Published: 2009-01-04 - Publisher: Princeton University Press

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In addition to econometric essentials, this book covers important new extensions as well as how to get standard errors right. The authors explain why fancier ec
Mastering 'Metrics
Language: en
Pages: 300
Authors: Joshua D. Angrist
Categories: Business & Economics
Type: BOOK - Published: 2014-12-21 - Publisher: Princeton University Press

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An accessible and fun guide to the essential tools of econometric research Applied econometrics, known to aficionados as 'metrics, is the original data science.
Causal Inference
Language: en
Pages: 585
Authors: Scott Cunningham
Categories: Business & Economics
Type: BOOK - Published: 2021-01-26 - Publisher: Yale University Press

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An accessible, contemporary introduction to the methods for determining cause and effect in the Social Sciences “Causation versus correlation has been the bas
Teaching Statistics
Language: en
Pages: 353
Authors: Andrew Gelman
Categories: Mathematics
Type: BOOK - Published: 2002-08-08 - Publisher: OUP Oxford

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Students in the sciences, economics, psychology, social sciences, and medicine take introductory statistics. Statistics is increasingly offered at the high scho
Regression and Other Stories
Language: en
Pages: 551
Authors: Andrew Gelman
Categories: Business & Economics
Type: BOOK - Published: 2020-07-23 - Publisher: Cambridge University Press

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A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference.